Today’s AI models can make decisions, call APIs, execute code and run operations in real time. That opens new possibilities for generative, agentic and physical AI, but doesn’t yet dictate how to go from capabilities to business value.
Governance is the new key to success. Data quality, evaluation, policy enforcement, adversarial testing and human expertise all shape how AI performs once it’s operating in live environments.
This Everest Group research report explores the right practices and operational foundations behind trustworthy AI, with a framework for moving from development and validation to deployment and ongoing operations.
What’s inside:
- The operational stack: Architectural requirements and monitoring models to govern physical and digital AI deployments
- Expert trust operations: Specialist human oversight to resolve complex regulatory issues, policy breaches and adversarial edge cases
- Partner strategy & risk allocation: Strategic criteria for leveraging external partners while retaining strict internal ownership of risk, safety and governance
